We aim to keep the number of hyperparameters low and therefore resist adopting additional data augmentation and regularization techniques. However, we found that drop path regularization [1]}, [2]} is highly effective for ViT backbones and therefore we include it (, it improves from-scratch training by up to 2 AP\(^\text{box}\) ).
